Prognostic Values of Core Genes in Pilocytic Astrocytom

World Neurosurg. 2023 Aug:176:e101-e108. doi: 10.1016/j.wneu.2023.05.006. Epub 2023 May 9.

Abstract

Background: Pilocytic astrocytoma (PA) is the most common primary brain tumor in children and adolescents. Treatment strategy largely depends on its key genes and molecular mutations. This study aimed to identify potential biomarkers of PA closely related to its prognosis.

Methods: The gene expression profiles (series numbers GSE50161, GSE66354, and GSE86574) of PA and normal brain tissues were downloaded from the Gene Expression Omnibus database. The Gene Expression Omnibus2R was used to identify differentially expressed genes. The overlapping differentially expressed genes were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. A protein-protein interaction network was constructed using Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. The Gene Expression Profiling Interactive Analysis 2 (GEPIA2) tool analyzed the impact of hub genes on PA prognosis based on the Kaplan-Meier curves.

Results: Compared with normal brain tissues (n = 36), a total of 37 upregulated and 144 downregulated genes were identified in PA (n = 40). In the protein-protein interaction network construction and GEPIA2 survival analysis, 2 of the top 10 hub genes were significantly associated with decreased overall survival of PA patients, namely Gamma-aminobutyric acid A receptor alpha 2 (hazard ratio = 2.8, P < 0.01) and regulating synaptic membrane exocytosis protein 1) (hazard ratio = 3.2, P < 0.01).

Conclusions: This bioinformatics analysis reveals that low expression of Gamma-aminobutyric acid A receptor alpha 2 and regulating synaptic membrane exocytosis protein 1 is associated with a favorable prognosis for PA patients. These 2 hub genes could be novel biomarkers for prognosis assessment, furthermore a key element for treatment decisions in the future.

Keywords: Bioinformatics analysis; Differentially expressed genes; Overall survival; Pilocytic astrocytoma.

MeSH terms

  • Adolescent
  • Biomarkers, Tumor* / genetics
  • Biomarkers, Tumor* / metabolism
  • Child
  • Computational Biology
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic / genetics
  • Humans
  • Prognosis
  • Protein Interaction Maps* / genetics
  • gamma-Aminobutyric Acid / metabolism

Substances

  • Biomarkers, Tumor
  • gamma-Aminobutyric Acid